Abstract: At approximately 3:45 a.m. on June 12, 1985, the catastrophic Xintan Landslide occurred. This event was successfully predicted in advance, resulting in no human casualties—a landmark achievement in global landslide early warning that has provided valuable insights for landslide hazard prevention and mitigation. Based on geological surveys and monitoring data, combined with analysis of both internal and external dynamic factors affecting the landslide, this study systematically investigated the disaster-inducing factors, failure process, and catastrophic mechanisms of the Xintan Landslide. It summarized the deformation patterns, pre-failure characteristics, successful prediction prcess, and lessons learned from the event. With the rapid development of big data and artificial intelligence technologies, research on landslide early warning and prediction through multi-technology collaborative monitoring, multi-source data fusion, and both data-driven and mechanism-driven approaches has become an important research direction. This study identifies key issues requiring further investigation in the study of collapse-loaded accumulation landslides, including: (1)risk assessment methodologies for such landslides, (2)evolution mechanisms and prevention strategies for high-speed debris flows in alpine valley regions, and(3)monitoring and early warning systems for collapse-loaded accumulation landslides. These findings provide valuable references for disaster prevention and mitigation of collapse-loaded accumulation landslides.